This book traces Heidegger's influence on a variety of political movements to fundamental ambiguities in his understanding of everydayness and nihilism.
In this fresh interpretation of Heidegger, Alexander S. Duff explains Heidegger's perplexing and highly varied political influence. Heidegger and Politics argues that Heidegger's political import is forecast by fundamental ambiguities about the status of politics in his thought. Duff explores how, in Being and Time as well as earlier and later works, Heidegger analyzes 'everyday' human existence as both irretrievably banal but also supplying our only tenuous path to the deepest questions about human life. Heidegger thus points to two irreconcilable attitudes toward politics: either a total and purifying revolution must usher in an authentic communal existence, or else we must await a future deliverance from the present dispensation of Being. Neither attitude is conducive to moderate politics, and so Heidegger's influence tends towards extremism of one form or another, modified only by explicit departures from his thought.
A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics. Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.
In recent years, increasing concern has been voiced about the nature and extent of human experimentation and its impact on the investigator, subject, science, and society. This casebook represents the first attempt to provide comprehensive materials for studying the human experimentation process. Through case studies from medicine, biology, psychology, sociology, and law—as well as evaluative materials from many other disciplines—Dr. Katz examines the problems raised by human experimentation from the vantage points of each of its major participants—investigator, subject, professions, and state. He analyzes what kinds of authority should be delegated to these participants in the formulation, administration, and review of the human experimentation process. Alternative proposals, from allowing investigators a completely free hand to imposing centralized governmental control, are examined from both theoretical and practical perspectives. The conceptual framework of Experimentation with Human Beings is designed to facilitate not only the analysis of such concepts as "harm," "benefit," and "informed consent," but also the exploration of the problems raised by man's quest for knowledge and mastery, his willingness to risk human life, and his readiness to delegate authority to professionals and rely on their judgment.
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